Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 204 164 724 546 631 526 874 77 914 174 453 455 103 528 913 471 960 74 710 529
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] NA 710 914 874 204 164 NA 529 528 546 526 913 724 NA 631 77 453 174 471 74 455 103 960
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 3 4 5 3 3 2 4 1 5
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "r" "e" "c" "l" "b" "N" "G" "J" "A" "H"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 9 15 17
which( manyNumbersWithNA > 900 )
[1] 3 12 23
which( is.na( manyNumbersWithNA ) )
[1] 1 7 14
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 914 913 960
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 914 913 960
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 914 913 960
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "N" "G" "J" "A" "H"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "r" "e" "c" "l" "b"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE FALSE TRUE FALSE
[18] FALSE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 4 6 11 12 14 16 20
sum( manyNumbers %in% 300:600 )
[1] 7
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] NA "large" "large" "large" "small" "small" NA "large" "large" "large" "large" "large" "large"
[14] NA "large" "small" "small" "small" "small" "small" "small" "small" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "UNKNOWN" "large" "large" "large" "small" "small" "UNKNOWN" "large" "large" "large"
[11] "large" "large" "large" "UNKNOWN" "large" "small" "small" "small" "small" "small"
[21] "small" "small" "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] NA 710 914 874 0 0 NA 529 528 546 526 913 724 NA 631 0 0 0 0 0 0 0 960
unique( duplicatedNumbers )
[1] 2 3 4 5 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 3 4 5 1
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE TRUE
which.max( manyNumbersWithNA )
[1] 23
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 960
which.min( manyNumbersWithNA )
[1] 20
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 74
range( manyNumbersWithNA, na.rm = TRUE )
[1] 74 960
manyNumbersWithNA
[1] NA 710 914 874 204 164 NA 529 528 546 526 913 724 NA 631 77 453 174 471 74 455 103 960
sort( manyNumbersWithNA )
[1] 74 77 103 164 174 204 453 455 471 526 528 529 546 631 710 724 874 913 914 960
sort( manyNumbersWithNA, na.last = TRUE )
[1] 74 77 103 164 174 204 453 455 471 526 528 529 546 631 710 724 874 913 914 960 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 960 914 913 874 724 710 631 546 529 528 526 471 455 453 204 174 164 103 77 74 NA NA NA
manyNumbersWithNA[1:5]
[1] NA 710 914 874 204
order( manyNumbersWithNA[1:5] )
[1] 5 2 4 3 1
rank( manyNumbersWithNA[1:5] )
[1] 5 2 4 3 1
sort( mixedLetters )
[1] "A" "b" "c" "e" "G" "H" "J" "l" "N" "r"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 5.5 3.0 3.0 10.0 3.0 8.0 5.5 8.0 8.0 1.0
rank( manyDuplicates, ties.method = "min" )
[1] 5 2 2 10 2 7 5 7 7 1
rank( manyDuplicates, ties.method = "random" )
[1] 5 3 4 10 2 7 6 9 8 1
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 0.1873370 -0.3493287 0.3487434 1.3830733
[10] 1.1596234 -1.8043173 -0.4060881 -0.2844329 -0.8486468 0.2763056
round( v, 0 )
[1] -1 0 0 0 1 0 0 0 1 1 -2 0 0 -1 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.2 -0.3 0.3 1.4 1.2 -1.8 -0.4 -0.3 -0.8 0.3
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.19 -0.35 0.35 1.38 1.16 -1.80 -0.41 -0.28 -0.85 0.28
floor( v )
[1] -1 -1 0 0 1 0 -1 0 1 1 -2 -1 -1 -1 0
ceiling( v )
[1] -1 0 0 1 1 1 0 1 2 2 -1 0 0 0 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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